A computational biologist's personal views on new technologies & publications on genomics & proteomics and their impact on drug discovery

Thursday, July 03, 2008

Myeloma unified?

Multiple myeloma is a complex disease. Perhaps one metaphor is that of the mythical Hydra -- each time a new molecular tool is thrown at it the number of vicious heads increases. For example, there are different chromosomal translocations which lead to myeloma. If you look at myeloma samples by transcriptional profiling, then one can find distinct expression signatures for each translocation -- and just as easily find ways to split those signatures into further subtypes. For example, some translocations activate one gene disrupted by the translocation whereas other instances of the same translocation will activate both deranged genes.

Another possible metaphor is the old fable of blind men examining an elephant -- each reports that the object is different, based on examining a different portion of the beast. In the case of myeloma, one examiner might focus on the subset with large portions of the genome amplified, others on specific deletions on chromosome 13, another on those cases where bone destruction is rampant. My own experience with palpitating the pachyderm looked at the response to a specific drug.

Now the Staudt lab has come out with a paper in Nature which proposes lumping everything back together again. Initially using a retroviral RNAi screen they identified the transcription factor IRF4 as a unifying theme of myeloma. IRF4 is activated in one characteristic translocation and plays an important role in B-cell development, so it's not a total shock. But linking it across multiple types is surprising.

The screen achieved 2-8 fold knockdown of IRF4 in 3 different myeloma cell lines, each possessing a different hallmark translocation (one of which was an IRF4 translocation). This was later extended to additional myeloma lines with similar lethality, but the knockdown of IRF4 in lymphoma lines had little effect, save one line possessing a translocation of IRF4.

One interesting surprise is that with the exception of the known IRF4 translocation bearing line, none of the lines have amplifications or other obvious derangements of IRF4. Only one showed point mutations upon resequencing. Hence, somehow IRF4 is being activated but not via a painfully obvious mechanism.

RNAi approaches can suffer from off-targets, genes not meant to be hit which cause the phenotype being studied rather than the believed target. The paper provides strong evidence that the effects really are driven by IRF4 knockdown -- not only were multiple shRNAs targeting IRF4 found to kill myeloma cells, but one of these targets the 3' untranslated region of IRF4 -- and the phenotype could be rescued by expressing IRF4 lacking the 3' UTR.

Transcriptional profiling of the knockdown lines in comparison with parental lines revealed a number of candidate IRF4 targets, and a large number of these were also identified by chromatin immunoprecipitation-chip (ChIP-chip) studies, confirming them as direct IRF4 targets. As noted, some direct targets may have been missed by ChIP-chip due to limitations with the arrays used. One other interesting aspect: the IRF4 target list in myeloma lines somewhat resembles a union of that in plasma cells (the normal cell myelomas are most kin to) with that of antigen-stimulated B-cells.

A particularly interesting direct IRF4 target identified in this study is the notorious oncogene MYC. A number of identified IRF4 targets are also known MYC targets, suggesting synergistic activation. They also found that both IRF4 and MYC bind upstream of IRF4 -- suggesting a complex web of positive feedback loops.

An interesting further bit of work targeted various identified IRF4 targets and showed these knockdowns to be lethal to myeloma cell lines. Hence it is suggested that IRF4 ablation in myeloma would lead to tumor cell death by many routes. Mice heterozygous for IRF4 deletion are viable, suggesting that IRF4 could be targeted safely.

The catch would be targeting IRF4 -- transcription factors are on nobody's list of favorite targets. The authors cite as points of optimism approaches targeting p53 & BCL6. However, the p53 targeting route is by inhibiting an enzyme which destabilizes p53, so an analogous approach to IRF4 would require first identifying key determinants of its stability. The BCL6 example they cite uses a peptide mimic, not something the medicinal chemists love much.

Other approaches to targeting IRF4 might focus on "druggable" (if any) genes in the IRF4 target lists, or perhaps something else. I'll try to put together a post next week on one of those candidate elses.

Now that Staudt's group has brought things together, it is tempting to contemplate slicing off some more Hydra heads. How do IRF4 target gene profiles differ across the chromosomal abberation subtypes of myleoma? Do IRF4 targets have any predictive value for determining the appropriate medication or show differential response to different medications?

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About Me

Dr. Robison spent 10 years at Millennium Pharmaceuticals working with various genomics & proteomics technologies & working on multiple teams attempting to apply these throughout the drug discovery process. He spent 2 years at Codon Devices working on a variety of protein & metabolic engineering projects as well as monitoring a high-throughput gene synthesis facility. After a brief bit of consulting, he rejoined the cancer drug discovery field at Infinity Pharmaceuticals in May 2009. In September 2011 he joined Warp Drive Bio, a startup applying genomics to natural product drug discovery. Other recurring characters in this blog are his loyal Shih Tzu Amanda and his teenaged son alias TNG (The Next Generation).
Dr. Robison can be reached via his Gmail account, keith.e.robison@gmail.com
You can also follow him on Twitter as @OmicsOmicsBlog.